Category Archives: Malnutrition

Gari T, Loha E, Deressa W, Solomon T, Lindtjørn B (2018) Malaria increased the risk of stunting and wasting among young children in Ethiopia: Results of a cohort study.PLoS ONE 13(1): e0190983.

AbstractIntroductionGiven the high prevalence of malnutrition in a malaria-endemic setting, improving nutritional status could serve as a tool to prevent malaria. However, the relationship between the two conditions remains unclear. Therefore, this study assessed the association between under-nutrition and malaria among a cohort of children aged 6 to 59 months old.

Methods Two cohorts of children were followed for 89 weeks in a rural Rift Valley area of Ethiopia. In the first approach (malaria-malnutrition), a cohort of 2,330 non-stunted and 4,204 non-wasted children were included to assess under-nutrition (outcome) based on their previous malaria status (exposure). In the second approach (malnutrition–malaria), a cohort of 4,468 children were followed-up to measure malaria (outcome), taking under-nutrition as an exposure. A weekly home visit was carried out to identify malaria cases. Four anthropometry surveys were conducted, and generalized estimating equation (GEE) method was used to measure the association between undernutrition and malaria.

Results The prevalence of stunting was 44.9% in December 2014, 51.5% in August 2015, 50.7% in December 2015 and 48.1% in August 2016. We observed 103 cases with 118 episodes of malaria, 684 new stunting and 239 new wasting cases. The incidence rate per 10,000 weeks of observation was 3.8 for malaria, 50.4 for stunting and 8.2 for wasting. Children with malaria infection, [Adjusted Odds Ratio (AOR) = 1.9; 95% Confidence Interval (CI), 1.2–2.9)] and younger age (AOR = 1.3; 95% CI, 1.1–1.5) were more likely to be stunted. Furthermore, children with malaria infection (AOR = 8.5; 95% CI, 5.0–14.5) and young age group (AOR = 1.6; 95% CI, 1.2–2.1) were more likely to be wasted. However, stunting and wasting were not risk factors of subsequent malaria illness.

Conclusions Malaria infection was a risk factor for stunting and wasting, but stunting or wasting was not associated with subsequent malaria illness. As our study shows that malaria is a risk factor for stunting and wasting, a close follow-up of the nutritional status of such children may be needed.

Objective: We aimed to evaluate the association between household food insecurity and maternal depression in Ethiopia.

Design/Setting/Subjects: In 2014, we conducted a cross-sectional study in southern Ethiopia, including 591 food-secure and 2500 food-insecure households. We measured depression status of women using the Patient Health Questionnaire-9 validated for Ethiopia, with a cut-off of ≥5. We evaluated household-level food insecurity using a validated Household Food Insecurity Access Scale. We applied Bayesian modelling to evaluate the relationship between food insecurity and maternal depression accounting for other observed characteristics.

Conclusions: The study documented a high burden of depression among women who lived in food-insecure households. Given this finding, we recommend integrating mental health in the livelihood programmes in areas suffering from food insecurity.

Introduction As part of a field trial (PACTR201411000882128) to provide evidence on the combined use of long-lasting insecticidal nets and indoor residual spray for malaria prevention, we measured haemoglobin values among children aged 6 to 59 months. The aim of this study was to estimate the prevalence of anaemia, and to determine the risk factors of anaemia and change in haemoglobin value in Adami Tullu district in south-central Ethiopia.

Methods Repeated cross-sectional surveys among 2984 children in 2014 and 3128 children in 2015; and a cohort study (malaria as exposure and anaemia as outcome variable) were conducted. The study area faced severe drought and food shortages in 2015. Anaemia was diagnosed using HemoCue Hb 301, and children with haemoglobin <11 g/dl were classified as anaemic. Multilevel and Cox regression models were applied to assess predictors of anaemia.

Results The prevalence of anaemia was 28.2% [95% Confidence Interval (CI), 26.6–29.8] in 2014 and increased to 36.8% (95% CI, 35.1–38.5) in 2015 (P<0.001). The incidence of anaemia was 30; (95% CI, 28–32) cases per 100 children years of observation. The risk of anaemia was high (adjusted Hazard Ratio = 10) among children with malaria. Children from poor families [Adjusted Odds Ratio (AOR); 1.3; 95% CI, 1.1–1.6)], stunted children (AOR 1.5; 95% CI; 1.2–1.8), and children aged less than 36 months (AOR; 2.0; 95% CI, 1.6–2.4) were at risk of anaemia compared to their counterparts. There was no significant difference in risk of anaemia among the trial arms.

Conclusions Young age, stunting, malaria and poverty were the main predictors of anaemia. An increase in the prevalence of anaemia was observed over a year, despite malaria prevention effort, which could be related to the drought and food shortage. Therefore, conducting trials in settings prone to drought and famine may bring unexpected challenges.

Hagos S, Hailemariam D, WoldeHanna T, Lindtjørn B (2017) Spatial heterogeneity and risk factors for stunting among children under age five in Ethiopia: A Bayesian geo-statistical model. PLOS ONE 12(2): e0170785. doi: 10.1371/journal.pone.0170785

Background Understanding the spatial distribution of stunting and underlying factors operating at meso-scale is of paramount importance for intervention designing and implementations. Yet, little is known about the spatial distribution of stunting and some discrepancies are documented on the relative importance of reported risk factors. Therefore, the present study aims at exploring the spatial distribution of stunting at meso- (district) scale, and evaluates the effect of spatial dependency on the identification of risk factors and their relative contribution to the occurrence of stunting and severe stunting in a rural area of Ethiopia.

Methods A community based cross sectional study was conducted to measure the occurrence of stunting and severe stunting among children aged 0–59 months. Additionally, we collected relevant information on anthropometric measures, dietary habits, parent and child-related demographic and socio-economic status. Latitude and longitude of surveyed households were also recorded. Local Anselin Moran’s I was calculated to investigate the spatial variation of stunting prevalence and identify potential local pockets (hotspots) of high prevalence. Finally, we employed a Bayesian geo-statistical model, which accounted for spatial dependency structure in the data, to identify potential risk factors for stunting in the study area.

Results Overall, the prevalence of stunting and severe stunting in the district was 43.7% [95%CI: 40.9, 46.4] and 21.3% [95%CI: 19.5, 23.3] respectively. We identified statistically significant clusters of high prevalence of stunting (hotspots) in the eastern part of the district and clusters of low prevalence (cold spots) in the western. We found out that the inclusion of spatial structure of the data into the Bayesian model has shown to improve the fit for stunting model. The Bayesian geo-statistical model indicated that the risk of stunting increased as the child’s age increased (OR 4.74; 95% Bayesian credible interval [BCI]:3.35–6.58) and among boys (OR 1.28; 95%BCI; 1.12–1.45). However, maternal education and household food security were found to be protective against stunting and severe stunting.

Conclusion Stunting prevalence may vary across space at different scale. For this, it’s important that nutrition studies and, more importantly, control interventions take into account this spatial heterogeneity in the distribution of nutritional deficits and their underlying associated factors. The findings of this study also indicated that interventions integrating household food insecurity in nutrition programs in the district might help to avert the burden of stunting.

Background: Ethiopia is one of the countries with the highest burden of undernutrition, with rates of stunting and underweight as high as 40% and 25%, respectively. National efforts are underway for an accelerated reduction of undernutrition by the year 2030. However, for this to occur, understanding the spatial variations in the distribution of undernutrition on a varying geographic scale, and its determinants will contribute a quite a bit to enhance planning and implementing nutrition intervention programmes.

Objectives: The aim of this thesis was to evaluate the large- and small-scale spatial variations in the distribution of undernutrition indicators, the underlying processes and the factors responsible for the observed spatial variations.

Methods: We used nationally available climate and undernutrition data to evaluate the macro-scale spatial pattern of undernutrition and its determinants. We applied a panel study design, and evaluated the effect of growing seasonal rainfall and temperature variability on the macro-scale spatial variations (Paper I). We conducted a repeated cross- sectional survey to assess the performance of the Household Food Insecurity Access Scale (HFIAS) developed internationally to measure household food insecurity. The results from this validation work were used to modify the HFIAS items for subsequent papers (Papers III and IV). We conducted a census on six randomly selected kebeles to evaluate the spatial patterns of undernutrition on a smaller scale (Paper III). For Paper IV, we conducted a cross-sectional survey on a representative sample, and employed a Bayesian geo-statistical model to help identify the risk factors for stunting, thereby accounting for the spatial structure (spatial dependency) of the data.

Results: In Paper I, we demonstrated spatial variations in the distribution of stunting across administrative zones in the country, which could be explained in part by rainfall. However, the models poorly explained the variation in stunting within an administrative zone during the study period. We indicated that a single model for all agro-ecologic zones may not be appropriate. In Paper II, we showed that the internal consistency of the HFIAS’ tools, as measured by Cronbach’s alpha, was adequate. We observed a lack of reproducibility in HFIAS score among rural households. Therefore, we modified the HFAIS tool, and used it for subsequent surveys in this thesis (Papers III and IV). In Paper III, spatial clustering on a smaller scale (within a kebele) was found for wasting and severe wasting. Spatial clustering on a higher scale (inter-kebele) was found for stunting and severe stunting. Children found within the identified cluster were 1.5 times more at risk of stunting, and nearly five times more at risk of wasting, than children residing outside this cluster. In Paper IV, we found a significant spatial heterogeneity in the distribution of stunting in the district. Using both the local Anselin Moran’s I (LISA) and the scan statistics, we identified statistically significant clusters of high value (hotspots) and a most likely significant cluster for stunting in the eastern part of the district. We found that the risk of stunting was higher among boys, children whose mother or guardian had no education and children who lived in a food-insecure household. We showed that including a spatial component (spatial structure of the data) into the Bayesian model improved the model fit compared with the model without this spatial component.

Conclusion: We demonstrated that stunting and wasting exhibited a spatial heterogeneity, both on a large and small scale, rather than being distributed randomly. We demonstrated that there is a tendency for undernourished cases (stunting and wasting) to occur near each other than to occur homogeneously. We demonstrated a micro-level spatial variation in risk and vulnerability to undernutrition in a district with a high burden of undernutrition. Identifying such areas where a population at risk lives is central in assisting a geographical targeting of intervention. We recommend further study, possibly using a trial design or implementation research approach, to help evaluate the feasibility and benefits of geographically targeting nutritional interventions.

As malnutrition is a major public health problem in Ethiopia, we aimed to find out how the acute and chronic forms of undernutrition occur in the districts and kebeles (a kebele is the smallest administrative unit in Ethiopia). Such knowledge could be helpful in improving our understanding of the distribution of undernutrition on a local scale, as well as designing targeted nutrition intervention programmes.

For this purpose, we surveyed children aged less than five years, who were found in 1744 households. We measured children’s height, weight, and the geographic locations (latitudes and longitudes) of households. Using data from 2371 children aged less than five years of age, we evaluated how malnutrition is distributed within a district and kebeles.

Although many believe that undernutrition is equally distributed within an area, we found that children living in locations within a district are more susceptible to undernutrition than children in other locations but living in the same district. For example, children living in these locations were 1.5 times more likely to be stunted and 1.7 times more likely to be severely stunted than children living in other locations within the district. Similarly, in some kebeles, children living in some small areas experience more acute malnutrition (wasting and severe wasting).

Our finding has important implications to nutritional intervention strategies. Stunting and wasting are not equally distributed in an area, suggesting that planning of nutrition interventions may need to consider the variations in the vulnerability.

To help accelerate the reduction of malnutrition, it could be important to consider targeting locations where more susceptible children live. The approach would help reach children who are most likely to benefit from intervention programmes.

We recommend that this research needs to be repeated in other areas of Ethiopia and other developing countries. We also would like to recommend further study possibly using an implementation research approach to evaluate the feasibility, advantages and effectiveness of targeting nutritional interventions.

Background: Malaria and malnutrition are the major causes of morbidity and mortality in under-five children in developing countries such as Ethiopia. Malnutrition is the associated cause for about half of the deaths that occur among under-five children in developing countries. However, the relationship between malnutrition and malaria is controversial still, and it has also not been well documented in Ethiopia. The aim of this study was to assess whether malnutrition is associated with malaria among under-five children.

Methods: A case–control study was conducted in Adami Tulu District of East Shewa Zone in Oromia Regional State, Ethiopia. Cases were all under-five children who are diagnosed with malaria at health posts and health centres. The diagnosis was made using either rapid diagnostic tests or microscopy. Controls were apparently healthy under-five children recruited from the community where cases resided. The selection of the controls was based on World Health Organization (WHO) cluster sampling method. A total of 428 children were included. Mothers/caretakers of under-five children were interviewed using pre-tested structured questionnaire prepared for this purpose. The nutritional status of the children was assessed using an anthropometric method and analyzed using WHO Anthro software. A multivariate logistic analysis model was used to determine predictors of malaria.

Results: Four hundred twenty eight under-five children comprising 107 cases and 321 controls were included in this study. Prevalence of wasting was higher among cases (17.8 %) than the controls (9.3 %). Similarly, the prevalence of stunting was 50.5 % and 45.2 % among cases and controls, respectively. Severe wasting [Adjusted Odds Ratio (AOR) =2.9, 95 % CI (1.14, 7.61)] and caretakers who had no education [AOR = 3, 95 % CI (1.27, 7.10)] were independently associated with malarial attack among under-five children.

Conclusion: Children who were severely wasted and had uneducated caretakers had higher odds of malarial attack. Therefore, special attention should be given for severely wasted children in the prevention and control of malaria.

Gebreyesus SH, Mariam DH, Woldehanna T, Lindtjorn B. Local spatial clustering of stunting and wasting among children under the age of 5 years: implications for intervention strategies. Public Health Nutr. 2015:1-11.

ObjectiveThe present study aimed to evaluate the clustering of undernutrition indicators of children under the age of 5 years in relation to different scales.

Design A community-based cross-sectional study design was employed. We collected anthropometric data, geographic locations/elevations of households and other data from visited households. We used a retrospective purely spatial Poisson probability model to identify and locate clusters (high rates) of stunting and wasting using the software SaTScan™ version 9·1·1. We ran a logistic regression model to help evaluate the causes of clustering.

SettingsSix villages in the Meskane Mareko District (38·45763°E, 8·042144°N) of southern Ethiopia.

Subjects We surveyed 2371 children aged <5 years, who were found in 1744 households.

Results We found a micro-level variation in the risk of stunting and wasting within the studied district. We found the most likely significant clusters for wasting and severe wasting in two of the six villages. For stunting, a single large cluster size of 390 cases (304·19 expected) in 756 households was identified (relative risk=1·48, P<0·01). For severe stunting, a single cluster size of 106 cases (69·39 expected) in 364 households was identified (relative risk=1·69, P=0·035).

Conclusions We conclude that the distribution of wasting and stunting was partly spatially structured. We identified distinct areas within and between villages that have a higher risk than the underlying at-risk population. Our analysis identified the spatial locations of high-risk areas for stunting that could be an input for geographically targeting and optimizing nutritional interventions.

AbstractBackground
The concept of food insecurity encompasses three dimensions. One of these dimensions, the access component of household food insecurity is measured through the use of the Household Food Insecurity Access Scale (HFIAS). Despite its application in Ethiopia and other similar developing countries, its performance is still poorly explored. Our study aims to evaluate the validity of the HFIAS in Ethiopia.

Methods
We conducted repeated cross-sectional studies in urban and rural villages of the Butajera District in southern Ethiopia. The validation was conducted on a pooled sample of 1,516 households, which were selected using a simple random sampling method. The HFIAS was translated into the local Amharic language and tested for face validity. We also evaluated the tool’s internal consistency using Cronbach’s alpha and factor analysis. We tested for parallelism on HFIAS item response curves across wealth status and further evaluated the presence of a dose-response relationship between the food insecurity level and the consumption of food items, as well as between household wealth status and food insecurity. Additionally, we evaluated the reproducibility of the tool through the first and second round of HFIAS scores.

Results
The HFIAS exhibited a good internal consistency (Cronbach’s alpha for the values of rounds 1 and 2 were 0.76 and 0.73, respectively). A factor analysis (varimax rotation) resulted in two main factors: the first factor described a level of mild to moderate food insecurity, while the second factor described severe food insecurity. HFIAS item response curves were parallel across wealth status in the sample households, with a dose-response trend between food insecurity levels and the likelihood of previous day food consumption being observed. The overall HFIAS score did not change over the two rounds of data collection.

Conclusions
The HFIAS is a simple and valid tool to measure the access component of household food insecurity. However, we recommend the adaptation of questions and wordings and adding examples before application, as we found a discrepancy in understanding of some of the nine HFIAS questions.

Background The amount and distribution of rainfall and temperature influences household food availability, thus increasing the risk of child undernutrition. However, few studies examined the local spatial variability and the impact of temperature and rainfall on child undernutrition at a smaller scale (resolution). We conducted this study to evaluate the effect of weather variables on child under nutrition and the variations in effects across the three agroecologies of Ethiopia.

Methods A longitudinal panel study was conducted. We used crop productions (cereals and oilseeds), livestock, monthly rainfall and temperature, and child under nutrition data for the period of 1996, 1998, 2000 and 2004. We applied panel regression fixed effects model.

Results The study included 43 clusters (administrative zones) and 145 observations. We observed a spatiotemporal variability of rainfall, stunting and underweight. We estimated that for a given zone, one standard deviation increase in rainfall leads to 0.242 standard deviations increase in moderate stunting. Additionally, a one standard deviation increase temperature leads to 0.216 standard deviations decrease in moderate stunting. However, wasting was found to be poorly related with rainfall and temperature. But severe wasting showed a positive relationship with the quadratic term of rainfall.

Conclusions We conclude that rainfall and temperature are partly predicting the variation in child stunting and underweight. Models vary in predicting stunting and underweight across the three agroecologic zones. This could indicate that a single model for the three agroecologies may not be not applicable.